Development, Implementation, and Evaluation of Treatment Guidelines for Herpes Simplex Keratitis in Sydney, Australia
Bibliographic record
Abstract
PURPOSE: To develop and measure the uptake of a local guideline for herpes simplex keratitis (HSK) and to standardize initial antiviral therapy in Australia. METHODS: The Registered Nurses' Association of Ontario Toolkit: "Implementation of Best Practice Guidelines" was used to develop, implement, and evaluate the guideline at Sydney Eye Hospital. An implementation team was established to reach consensus on antiviral therapy guidelines through review of available evidence, identifying stakeholders, facilitators and barriers, creating strategies for implementation, and developing a sustainability plan. An audit of all adult HSK cases during a 6-month postguideline implementation period was conducted, and the results were compared with a preimplementation audit. A web-based survey was created to assess clinician awareness, usage, and level of knowledge of the guideline. RESULTS: Clinicians, pharmacists, and administrative staff were identified as stakeholders. Changing clinician's behavior was the major barrier to implementation. Implementation strategies included printed and online materials and lectures to clinicians. A postimplementation audit included 85 patients, and 95 clinicians received a web-based survey. The dose of the prescribed antiviral medication was in alignment with the local guideline in 80% (51/64) of the patients compared with 73% (163/223) before implementation (P = 0.331). Stromal HSK with ulceration and keratouveitis were excluded because there were no recommendations before implementation. Over 70% of clinicians (30/41) were aware of the guideline and accessed them through educational resources. CONCLUSIONS: Guidelines for the management of HSK may improve standardization of initial antiviral therapy in HSK. In practice, most clinicians were aware of and adhered to the local guideline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.095 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".